AI Empowered Net-RCA for 6G

TL;DR

This paper proposes an AI-empowered network root cause analysis framework tailored for 6G networks, addressing the increased complexity and maintenance challenges with improved fault diagnosis capabilities.

Contribution

It introduces a novel AI-based Net-RCA framework specifically designed for 6G, outperforming existing methods in accuracy and efficiency.

Findings

Outperforms existing RCA methods on synthetic data

Demonstrates effectiveness on real-world network data

Reduces maintenance costs and efforts for 6G networks

Abstract

6G is envisioned to offer higher data rate, improved reliability, ubiquitous AI services, and support massive scale of connected devices. As a consequence, 6G will be much more complex than its predecessors. The growth of the system scale and complexity as well as the coexistence with the legacy networks and the diversified service requirements will inevitably incur huge maintenance cost and efforts for future 6G networks. Network Root Cause Analysis (Net-RCA) plays a critical role in identifying root causes of network faults. In this article, we first give an introduction about the envisioned 6G networks. Next, we discuss the challenges and potential solutions of 6G network operation and management, and comprehensively survey existing RCA methods. Then we propose an artificial intelligence (AI)-empowered Net-RCA framework for 6G. Performance comparisons on both synthetic and real-world network data are carried out to demonstrate that the proposed method outperforms the existing method considerably.